Physical systems, such as an electrical utility system or a heating, ventilation, and air conditioning (HVAC) system, may be monitored by a network of intelligent electronic devices (“IEDs”) coupled to a computer and/or server for monitoring various parameters or characteristics of the physical system. In addition to monitoring these systems, the physical systems may be modeled mathematically in a number of ways. Generally, the models take one or more observable qualities of the physical system that can be measured or observed and predict a numerical characterization of some other quality of the system that is thought to be causally influenced by the observed qualities. The observable qualities of the physical system that can be measured or observed are referred to as “driver variables,” or “independent variables.” The quality of the system that is thought to be causally influenced by the driver variables is called the “modeled variable,” or “dependent variable.”
One approach to modeling a physical system is by the use of a linear regression model, which computes a predicted quantity as a linear combination of scaled input quantities. However, some physical systems may have regimes of linear or piecewise linear behaviour each of which can be modeled well separately, but for which no single model will work for all of the regimes of applicability. The physical system may be modeled well using a linear model or a piecewise linear model with driver variables for each mode separately, but no single model can be constructed that works well for all modes.
Thus, a need exists for an improved system and method of modeling physical systems. The present invention is directed to satisfying one or more of these needs and solving other problems.